Application of multi-criteria analysis in the selection of formwork material for high-rise building construction projects

Figures & data

Figure 1. Research flowchart.

Figure 2. Various types of formworks in construction.

Table 1. Summary of excluded variables in the scale reliability assessment step.

Code	Excluded variables	References
F.06	Turnability	(Ahmed et al., 2012; Basu & Jha, 2016; Safa et al., 2018; Terzioglu et al., 2021b)
F.09	Easy to use	(Terzioglu et al., 2021b)
F.17	Ability to apply BIM to management	(Safa et al., 2018)

Figure 3. Multi-criteria decision making models.

Figure 4. The overall framework of MCDM models.

Table 2. Synthesis of studies related to MCDA methods for the FWS selection problem.

Problem	Method	Advantage	Reference
Selection of effective FWS	TOPSIS	Considered three types of currently used FWSs with eight decisive criteria that affect the choice of formwork selection	(Dhanasekar et al., 2019)
FWS selection in a real-life case study in Turkey	Rough AHP-EDAS	Consider the subjectivity and uncertainty arising from a group decision-making proces	(Terzioglu & Polat, 2022)
Contractors’ preference for FWS selection in Indonesia	AHP	Considerations for contractors to start using aluminium formwork due to its excellence compared to conventional timber formwork	(Hansen et al., 2020)
Select the most appropriate FWS	TOPSIS	Consider five most often used FWSs in the Polish construction sector	(Anna, 2015)
Selection of horizontal FWSs in Indian residential construction	AHP	Eighteen attributes were analyzed to identify six formwork selection factors. The most dominant factor governing the choice of a FWS for any construction project is ‘available capital and site characteristics’	(Basu & Jha, 2016)
FWS selection problem in Ecuador	Choosing by advantages (CBA)	Using 14 selection factors for the FWS selection problem in Ecuador, while additional FWS selection factors including FWS complexity and FWS size were added to the literature	(Martinez et al., 2016)
Selecting a formwork method suitable for construction site conditions in tall building construction projects	Boosted decision trees (BDTs)	Seven factors for selecting the horizontal form method were determined by interviewing engineers experienced in formwork in Korea	(Yoonseok et al., 2012)
Selection of vertical FWS	Probabilistic neural network (PNN)	Neural network models are developed for the selection of vertical FWSs network based on prior FWS selection factors	(Tam et al., 2005)
FWS selection for tall building construction	Adaboost Algorithm	Support the selection of a FWS that is suitable for the construction site conditions	(Shin, 2011)
Select horizontal and vertical FWSs	Fuzzy logic model	Based on five FWS selection factors determined to be the most significant in Egypt	(Elbeltagi et al., 2011; 2012)

Table 3. Summary of hybrid MCDA methods for the material selection problem.

Problem	Hybrid MCDM method	Area	Reference
Material for a cryogenic storage tank for transportation of liquid nitrogen	AHP, TOPSIS	Chemical	(Rao & Davim, 2008)
Plastic pipe material selection for water supply	AHP, GRA	Construction	(Zhao et al., 2016)
Material for a product designed for operating in a high temperature environment	AHP, VIKOR	Manufacturing	(Rao, 2008)
Material of hacksaw blade	AHP, PROMETHEE	Manufacturing	(Chothani et al., 2015)
Composite reinforcement for the manufacturing of screw rotor of air compressor	AHP, EVAMIX	Manufacturing	(Darji & Rao, 2013)
Automotive thermoplastic materials for passenger car	AHP and TOPSIS	Automotive	(Mansor et al., 2014)
Material of automobile bumper	FAHP, PROMETHEE	Automotive	(Ilangkumaran et al., 2013)
Material for design of an axle for a motorcycle	AHP, ANP	Automotive	(Sharma et al., 2015)

Table 4. Classification of criteria’s relative importance.

Priority	Numeric value
Equal priority	1
Prioritize with a little superiority	3
More priority	5
Very priority	7
Extremely priority	9
Intermediate level between the above levels	2, 4, 6, 8

Table 5. Priority of criteria according to expert opinion.

Criteria	1	2	…	n
1	$a_{11}$	$a_{12}$	…	$a_{1n}$
2	$a_{21}$	$a_{22}$	…	$a_{2n}$
…	…	…	…	…
n	$a_{n1}$	$a_{n2}$	…	$a_{\mathit{\text{nn}}}$

Table 6. Weighted mean matrix.

Criteria	1	2	…	n	Weight
1	$w_{11}$	$w_{12}$	…	$w_{1n}$	$w_1$
2	$w_{21}$	$w_{22}$	…	$w_{2n}$	$w_2$
…	…	…	…	…	…
n	$w_{n1}$	$w_{n2}$	…	$w_{\mathit{\text{nn}}}$	$w_n$

Table 7. Random Index corresponding number of factors (RI).

n	1	2	3	4	5	6	7	8	9	10
R	0	0	0.58	0.9	1.12	1.24	1.32	1.41	1.45	1.49

Table 8. Ranking of factors by impact level.

Code	Variables	References	Mean	Stad. Dev	Rank
C.01	Initial investment costs (purchase or lease)	(Elbeltagi et al., 2011; 2012; Safa et al., 2018)	4.33	0.748	1
P.01	Project completion time	(Rajeshkumar & Sreevidya, 2019)	4.17	0.972	2
C.02	Installation costs	(Rajeshkumar & Sreevidya, 2019)	4.08	0.722	3
P.02	Building shape	(Elbeltagi et al., 2012)	4.05	0.924	4
F.03	Formwork weight	(Martinez et al., 2016; U Din & Kumar, 2017)	4.02	0.756	5
F.05	Formwork tightness - ability of the FWS to prevent the leakage or seepage of concrete	(Expert opinion)	3.98	0.897	6
P.04	Total number of floors and floor height	(Rajeshkumar et al., 2021; Terzioglu et al., 2021b; Yoonseok et al., 2012)	3.89	0.866	7
F.04	Load capacity	(Krawczyńska-Piechna, 2016; Rajeshkumar & Sreevidya, 2019)	3.83	0.994	8
E.02	Site conditions and yard size	(Basu & Jha, 2016; Hanna et al., 1992)	3.82	0.727	9
F.07	Flexibility, high compatibility	(Krawczyńska-Piechna, 2016; Safa et al., 2018)	3.82	0.885	10
E.01	Weather and ambient conditions	(Hanna et al., 1992)	3.81	0.717	11
C.04	Maintenance and preservation costs	(Rajeshkumar & Sreevidya, 2019; Terzioglu et al., 2021b)	3.79	0.919	12
P.06	Available formwork	(Rajeshkumar & Sreevidya, 2019)	3.78	0.911	13
F.01	Formwork materials	(Naik & Rathod, 2015)	3.77	0.854	14
C.03	Transportation costs	(Rajeshkumar & Sreevidya, 2019; Terzioglu et al., 2021b)	3.76	0.882	15
P.03	Floor structure plan	(Hanna et al., 1992; Smith & Hanna, 1993)	3.76	0.951	16
F.02	Formwork quality	(Naik & Rathod, 2015)	3.76	0.984	17
P.07	Compatibility with construction machinery and equipment available on the construction site	(Safa et al., 2018)	3.73	0.902	18
E.03	Methods of storage, handling and preservation	(Rajeshkumar et al., 2021; Rajeshkumar & Sreevidya, 2019)	3.72	0.792	19
P.05	Quality of surface finished	(Martinez et al., 2016)	3.71	0.996	20
F.14	Construction productivity	(Terzioglu et al., 2021b)	3.68	0.852	21
F.15	Eco-friendly materials - renewable resources, recyclability, lightweight, durable, and long - lasting, etc.	(Expert opinion)	3.65	0.882	22
F.08	Level of complexity and number of accessories included	(Dongmin et al., 2018; Martinez et al., 2016; Safa et al., 2018)	3.64	0.86	23
F.10	Conformity with structures (foundation, columns, beams, floors, walls)	(Elbeltagi et al., 2011; Rajeshkumar & Sreevidya, 2019)	3.53	1.027	24
P.08	Reducing the overload for transport equipment when using advanced FWS	(Smith & Hanna, 1993)	3.51	0.975	25
F.13	Safety in construction	(Rajeshkumar & Sreevidya, 2019)	3.47	0.963	26
F.16	Recyclability	(Expert opinion)	3.42	0.938	27
F.12	Labor qualifications	(Expert opinion)	3.41	0.926	28
F.11	Construction speed	(Safa et al., 2018; Terzioglu et al., 2021b)	3.37	1.06	29
C.05	Liquidation value	(Expert opinion)	3.35	0.962	30

Figure 5. The Analytic Hierarchy Process model.

Table 9. Summary of priority evaluation among pairs of criteria according to expert opinion.

Criteria	TC1	TC2	TC3	TC4	TC5	TC6
TC1	1.000	4.714	4.714	5.143	6.714	7.286
TC2	0.212	1.000	0.215	0.263	0.199	6.571
TC3	0.212	4.641	1.000	3.857	4.571	6.286
TC4	0.194	3.798	0.259	1.000	5.000	5.429
TC5	0.149	5.030	0.219	0.200	1.000	6.286
TC6	0.137	0.152	0.159	0.184	0.159	1.000
Total	1.905	19.336	6.567	10.647	17.644	32.857

Table 10. Criteria weight when pairwise comparison.

Criteria	TC1	TC2	TC3	TC4	TC5	TC6	Weight
TC1	0.525	0.244	0.718	0.483	0.381	0.222	0.429
TC2	0.111	0.052	0.033	0.025	0.011	0.200	0.072
TC3	0.111	0.240	0.152	0.362	0.259	0.191	0.219
TC4	0.102	0.196	0.039	0.094	0.283	0.165	0.147
TC5	0.078	0.260	0.033	0.019	0.057	0.191	0.106
TC6	0.072	0.008	0.024	0.017	0.009	0.030	0.027
RI		λmax		CI		CR
1.24		6.047		0.009		0.8% < 10%

Table 11. Weighted criteria matrix 1.

TC1	Wood	Alu.	Plastic	Weight
Wood	1	0.206	0.155	0.082
Alu.	4.855	1	0.898	0.421
Plastic	6.454	1.114	1	0.497
RI	λmax	CI	CR
0.58	3.003	0.002	0.3% < 5%

Table 12. Weighted criteria matrix 2.

TC2	Wood	Alu.	Plastic	Weight
Wood	1	0.205	0.179	0.088
Alu.	4.884	1	1.357	0.492
Plastic	5.595	0.737	1	0.420
RI	λmax	CI	CR
0.58	3.022	0.011	1.9% < 5%

Table 13. Weighted criteria matrix 3.

TC3	Wood	Alu.	Plastic	Weight
Wood	1	0.231	0.182	0.093
Alu.	4.330	1	1.071	0.446
Plastic	5.480	0.933	1	0.461
RI	λmax	CI	CR
0.58	3.010	0.005	0.9% <5%

Table 14. Weighted criteria matrix 4.

TC4	Wood	Alu.	Plastic	Weight
Wood	1	0.193	0.159	0.080
Alu.	5.176	1	0.690	0.389
Plastic	6.289	1.448	1	0.531
RI	λmax	CI	CR
0.58	3.003	0.002	0.3% < 5%

Table 15. Weighted criteria matrix 5.

TC5	Wood	Alu.	Plastic	Weight
Wood	1	0.194	0.177	0.085
Alu.	5.149	1	0.845	0.425
Plastic	5.638	1.183	1	0.490
RI	λmax	CI	CR
0.58	3.001	0.0003	0.1% < 5%

Table 16. Weighted criteria matrix 6.

TC6	Wood	Alu.	Plastic	Weight
Wood	1	0.876	2.126	0.372
Alu.	1.141	1	3.262	0.469
Plastic	0.470	0.307	1	0.159
RI	λmax	CI	CR
0.58	3.010	0.005	0.8% < 5%

Table 17. Summary of calculation results.

	TC1	TC2	TC3	TC4	TC5	TC6
Wood	0.082	0.088	0.093	0.080	0.085	0.372
Alu.	0.421	0.492	0.446	0.389	0.425	0.469
Plastic	0.497	0.420	0.461	0.531	0.490	0.159

Table 18. Weighted criteria matrix.

Criteria	TC1	TC2	TC3	TC4	TC5	TC6
Weight	0.429	0.072	0.219	0.147	0.106	0.027

Table 19. Weight results of formwork selection alternatives.

Wood	0.093
Alu.	0.429
Plastic	0.479

Table 20. Characteristic comparison of some formwork types.

	Wood formwork	Aluminum formwork	Plastic formwork
Construction speed	12 days/floor (Dong, 2016)	4–5 days/floor (Ismail, 2008)	4 days/floor (Sowndharya & Vidhya, 2022)
Labor	70–80 people/1000m2 and need carpenters (Gazali, 2018)	40–50 people/1000m2 and no specific skills are required (Gazali, 2018)	unskilled labor (Asadi & Praneeth, 2017)
Weight	10 kg/m^2	+/-20 kg/m^2	7 kg/m^2
Durability	about 8 times reused, wood material is usually not durable and easily damaged when dismantled (Prajapati et al., 2014; Pratama et al., 2017)	100–150 times reused. More than 80% of materials can be used for other works (Poon et al., 2003; Sowndharya & Vidhya, 2022)​	more than 100 times reused, resistant to environmental and chemical corrosion (Ismail, 2008; Prajapati et al., 2014)
Cost	Low initial cost but high labor cost (Pratama et al., 2017; Rajeshkumar et al., 2021)	Relatively high initial cost but become cheaper with reuse (Poon et al., 2003)	Low maintenance cost (Sowndharya & Vidhya, 2022)
Surface quality	Joints between beams and columns can be seen. Need plastering or finishing coating to smooth the concrete surface (Jayasinghe & Fernando, 2017)	Smooth concrete surface, no visible joints, rarely need plastering (Jayasinghe & Fernando, 2017)	Smooth surface finished with small seams and no plaster required (Prajapati et al., 2014)
Flexibility	Very flexible. Can be easily cut, bent and modified to the required shape of the member (Ismail, 2008)	Need more modification time, easy to handle but with more joints (Ismail, 2008)	Available for any size and shape (Prajapati et al., 2014)
Waste	Generate a lot of wood waste and is not recyclable (Gazali, 2018; Ismail, 2008)	Reduce mortar and concrete debris, generate less construction waste (Poon et al., 2003)	Recyclability about 40% (Prajapati et al., 2014)
Planning	No detailed planning/drawing required (Gazali, 2018)	Detailed planning required (Poon et al., 2003)	Detailed design and planning required (Asadi & Praneeth, 2017)

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Data availability statement

The Data generated in this research are available from the corresponding author on request.